Rabies is a deadly and terrifying disease that kills over 59,000 people worldwide each year. Elimination of rabies is feasible through vaccination, and oral rabies vaccination (ORV) campaigns have eliminated fox rabies from Western Europe. However, there is little scientific guidance on where and when vaccination campaigns should be placed to eliminate rabies and prevent the disease from reinfecting rabies-free areas.
Spatial models capable of capturing local infection dynamics in wildlife populations have great potential to improve the planning of control programmes. However, developing models that can capture and explain spatiotemporal infectious processes at a local level remains a challenge due to a lack of high-resolution spatial and temporal data and limited population and surveillance data.
Together with Elias Krainski, I am developing a space-time model in R-INLA fit to geo-referenced monthly rabies cases prior to the start of oral rabies vaccinations (1982-1990) to capture the spatiotemporal dynamics of rabies and estimate the spatial dependence between rabies cases. Estimates of the spatial dependence between rabies cases derived from this approach will allow us to understand the spatial scale of transmission and inform control strategies by identifying areas of high prevalence where there is a greater risk of infection. In this talk I will present the current model and future plans to extend the model to capture and explore vaccination strategies.